# ----------------------------------------------------------------------------
# Title:   Scientific Visualisation - Python & Matplotlib
# Author:  Nicolas P. Rougier
# License: BSD
# ----------------------------------------------------------------------------
import numpy as np
import matplotlib.pyplot as plt

cmaps = ('tab10', 'tab20', 'tab20b', 'tab20c',
         'Pastel1', 'Pastel2', 'Paired',
         'Set1', 'Set2', 'Set3', 'Accent', 'Dark2' )

n = len(cmaps)

fig = plt.figure(figsize=(4.25, n*.22))
ax = plt.subplot(1, 1, 1, frameon=False,
                 xlim=[0,10], xticks=[], yticks=[])
fig.subplots_adjust(top=0.99, bottom=0.01, left=0.18, right=0.99)

y, dy, pad = 0, 0.5, 0.1
ticks, labels = [], []
for cmap in cmaps[::-1]:
    Z = np.linspace(0,1,512).reshape(1,512)
    plt.imshow(Z, extent=[0,10,y,y+dy], cmap=plt.get_cmap(cmap))
    ticks.append(y+dy/2)
    labels.append(cmap)
    y = y + dy + pad

ax.set_ylim(-pad,y)
ax.set_yticks(ticks)
ax.set_yticklabels(labels)
ax.tick_params(axis='y', which='both', length=0, labelsize="small")

plt.savefig("reference-colormap-qualitative.pdf", dpi=600)
plt.show()